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The Complex Story of Race and Upward Mobility

By David Leonhardt July 25, 2013 12:12 pmJuly 25, 2013 12:12 pm

Updated, 7:35 p.m. |

As my colleagues and I were working on our recent article and graphics about a new study on upward mobility, we found ourselves wondering how big a role race played. When you look at our interactive map showing upward-mobility rates by metropolitan area, you can see why.

Many of the areas where climbing the economic ladder is most difficult are also the areas with the largest concentration of African-Americans.

In this map, which ran in Monday’s Times, regions shaded red have low rates of upward mobility; regions shaded yellow have rates in the middle, and blue regions have the highest:

The metropolitan areas with the highest percentage of African-Americans are clustered in the southeast and the industrial Midwest. So are the metropolitan areas where low-income children have the longest odds of making it into the middle class.

Mecklenburg County in North Carolina – the heart of the Charlotte region, which ranks dead last in upward mobility among the 50th largest metropolitan regions, according to the study – is 32 percent black. Georgia’s Fulton County – home to Atlanta, which ranks 49th in mobility among the 50th biggest metropolitan regions – is 45 percent black. Indiana’s Marion County – site of Indianapolis, which ranks 48th – is 27 percent black.

In areas like these, fewer than one in 20 children born into a family into the bottom fifth of the income distribution in the early 1980s has made it to the top fifth as adults, the study found. By contrast, in the regions with the highest mobility, the chances can exceed one in 10. Those regions include some of the whitest parts of the country, like Utah, Idaho, Minnesota, the Dakotas and upper New England.

Yet the economists who did the study do not list race as one of the main factors that explains the variation in upward-mobility rates across regions. How could this be?

The simplest way to explain their conclusion may be to point out that upward mobility tends to be rare for both blacks and whites, as well as for Latinos, in low-mobility areas. In Charlotte, Atlanta and Indianapolis, low-income white children have also tended to grow up to be low-income adults.

To help demonstrate this pattern, the four researchers – Raj Chetty and Nathaniel Hendren of Harvard and Patrick Kline and Emmanuel Saez of the University of California, Berkeley – have produced another map, showing mobility only for ZIP codes that are at least 80 percent white. (Regions in which no ZIP codes are at least 80 percent white simply appear as blank on the map.)

Photo

From "The Economic Impacts of Tax Expenditures: Evidence from Spatial Variation Across the U.S.," by Raj Chetty, Nathaniel Hendren, Patrick Kline and Emmanuel Saez.Credit

The numbers on this map will have little meaning to most readers; they are statistical correlations between family income in one generation and family income in the next. But the message is clear: the mobility patterns look overwhelmingly similar in this map and in the map above showing all metropolitan areas.

It’s worth pointing out that race may still play a role in creating these patterns. “Racial shares in an area do matter,” Mr. Chetty says. “But it’s not race at the individual level. It’s race at the level of the ‘commuting zone,’” he added, using the researchers’ term for a region. Whatever the differences are between high-mobility and low-mobility regions, they seem to apply to residents of every race.

One possibility is that areas with large black populations tend to be more economically segregated, with poor residents – of all races – more likely to be isolated from the rich and middle class. Isolation can damage a low-income family’s chances in many ways, as the Atlanta residents I interviewed explained.

Writing about the new study for The Atlantic, Matthew O’Brien laid out a specific case for how race might have created economic segregation in sprawl-filled regions:

Atlanta, of course, is the prototypical case here: going back to the 1970s, it’s under-invested in public transit, because car-driving suburbanites haven’t wanted to pay for something they think only poor blacks would use (to come, they fear, to their lily-white cul-de-sacs). Even last year, a compromise bill that would have increased the sales tax by 1 percentage point for 10 years to pay for expanded roads and railways in the always-congested city got voted down. This malign neglect of infrastructure keeps low-income people from living near or commuting to better jobs — and that’s not a race issue. Indeed, the researchers also found that whites and blacks in Atlanta both have a hard time moving up. In other words, racial polarization might spur sprawl, which makes cities less likely to invest in their infrastructure — and underfunded infrastructure hurts low-income people of all races.

Whatever the precise answer, I assume that economic mobility may have something in common with many other subjects in American life: race matters, but not necessarily in the most obvious ways.

Update: I wanted to answer one question raised by a commenter, below. Steve Sailer writes: The final map in this posting doesn’t appear to show what it’s supposed to show: “Regions in which no ZIP codes are at least 80 percent white simply appear as blank on the map.” Yet, California, which is majority minority, is shown having no sectors that are blank gray. Is California really uniformly more than 80% non-Hispanic white?”

In this map, the authors assigned an entire metropolitan region — or “commuting zone,” to use their preferred term — a level of mobility based on the subset of ZIP codes without that region that had a population at least 80 percent white. To have a blank spot on the map, a region has to have zero codes that are at least 80 percent white. Relatively few regions qualify — and as Mr. Sailer notes, no regions in California.

The larger way of thinking about this map is that is an attempt to estimate what mobility looks like, across the country, for white people. The anonymous nature of the data does not allow the researchers to know who is white and who is not. Focusing on predominantly white ZIP codes offers a proxy. The researchers point out that when they look only at ZIP codes that are at least 95 percent white, they find very similar results, increasing their confidence that the 80-percent measure is a meaningful proxy for overall white mobility rates.

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